AM-09 - Classification and Clustering

Classification and clustering are often confused with each other, or used interchangeably. Clustering and classification are distinguished by whether the number and type of classes are known beforehand (classification), or if they are learned from the data (clustering). The overarching goal of classification and clustering is to place observations into groups that share similar characteristics while maximizing the separation of the groups that are dissimilar to each other. Clusters are found in environmental and social applications, and classification is a common way of organizing information. Both are used in many areas of GIS including spatial cluster detection, remote sensing classification, cartography, and spatial analysis. Cartographic classification methods present a simplified way to examine some classification and clustering methods, and these will be explored in more depth with example applications.
DA-13 - GIS&T in Criminal Justice and Law Enforcement
Linking crime and place has been the objective of crime mapping since the early nineteenth century. Contemporary scholars have since investigated spatio-temporal crime patterns to explain why crime concentrates in certain places during certain times. Collectively, this body of research has identified various environmental and situational factors that contribute to the formation of crime hot spots and spawned widespread crime prevention and reduction strategies commonly referred to as place-based policing. Environmental criminology guides the bulk of this crime-and-place research and provides a means for interpreting place and crime. The chapter details theories behind place-based policing, examples of place-based policing strategies that leverage geographic information science and its associated technologies (GIS&T), and relevant data visualization tools used by law enforcement to implement place-based strategies to address crime.